Comparar métodos

	Prob-ARAS	Processo de Hierarquia Analítica	Processo Analítico de Rede (AHP com feedback e interdependências)	Bayesian BWM
Área	Tomada de decisão	Tomada de decisão	Tomada de decisão	Tomada de decisão
Família	MCDM	MCDM	MCDM	MCDM
Ano de origem	2010	1980	1996	2020
Autor original	Zavadskas, E. K. Turskis, Z.	Saaty, T. L.	Saaty, T. L.	Mohammadi, M., Rezaei, J.
Tipo	Monte Carlo / stochastic weight uncertainty extension of ARAS	Pairwise comparison (eigenvalue)	Weight_Subjective (pairwise comparison, supermatrix, network structure)	Hierarchical Dirichlet posterior over weights via MCMC (JAGS) — group decision
Fonte seminal	Zavadskas, E. K., Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technological and Economic Development of Economy	Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York ISBN: 978-0070543713	Saaty, T. L. (1996). Decision Making with Dependence and Feedback: The Analytic Network Process. RWS Publications, Pittsburgh ISBN: 0-9620317-9-8	Mohammadi, M., Rezaei, J. (2020). Bayesian best-worst method: A probabilistic group decision making model. Omega
Outros nomes	—	—	—	—
Relacionados	8	8	8	8
Resumo	PROB-ARAS (Prob-ARAS — Stochastic extension of PROB-ARAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Zavadskas, E. K. Turskis, Z. in 2010. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	AHP (Analytic Hierarchy Process) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1980. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	ANP (Analytic Network Process (AHP with feedback and interdependences)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Saaty, T. L. in 1996. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.	BWM-BAYESIAN (Bayesian BWM — Probabilistic Group Best-Worst Method) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Mohammadi, M., Rezaei, J. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.